Data quality methodology

The data quality methodology information is organized by analytical function and provides in-depth knowledge and best practices for your data quality strategy.

There are a number of key concepts with data quality analysis and monitoring that include capabilities to:

Support business-driven rule definition and organization
Apply rules and reuse consistently across data sources
Leverage multi-level rule analysis to understand broader data quality issues
Evaluate rules against defined benchmarks/thresholds
Assess and annotate data quality results
Monitor trends in data quality over time
Deploy rules across environments
Run data quality activities on either an impromptu or scheduled basis using either the user interface or the command line